چکیده مقاله
In this research, to predict the amount of water consumption demand , the artificial neural network ANN equipped with discrete wavelet transform DWT function and a new model named W ANN is proposed In addition, Pierson correlation coefficient is applied for finding the proper input data set Here, data set includes temperature, precipitation, humidity and the amount of daily water produced from the beginning of 2014 to the end of 2019 To evaluate the performance of the models, statistical indices including R², RMSE and NSE have been calculated Comparison of the results showed that using discrete wavelet transform function to proposed W ANN model improves the performance of the proposed models and their results In addition, best results are obtained by using W ANN model In which for training data, the RMSE, NSE, R2 values are 2877 37 MCM , 0 83 and 0 86, and for test data are 3470 81 MCM , 0 74 and 0 76
کلیدواژهها
نویسندگان
Mohammadreza Alikhani
M sc, Department of Civil Engineering, Faculty of civil engineering and transportation, Universityof Isfahan, Isfahan, Iran
رامتین معینی
Associate Professor, Department of Civil Engineering, Faculty of civil engineering andtransportation, University of Isfahan, Isfahan, Iran
شیوه ارجاع
Alikhani, Mohammadreza and Moeini, Ramtin,1402,Predicting the drinking water consumption by equipping hybrid artificial neural network with discrete wavelet transform,13th International Congress on Civil Engineering,Tehran
ارائهشده در
مجموعه مقالات سیزدهمین کنگره بین المللی مهندسی عمران25 مهر 1402 · تهران